控制系统

设计、测试和实现控制系统

作为控制系统工程师，您可以在开发的所有阶段使用 MATLAB^® 和 Simulink^®，包括被控对象建模、控制器设计、自动代码生成部署和系统验证。使用 MATLAB 和 Simulink 控制系统产品，您可以：

使用基本模型、系统辨识或自动参数估计对线性和非线性被控对象动态特性进行建模。
配平、线性化和计算非线性 Simulink 模型的频率响应。
使用根轨迹、波特图、LQR、LQG 和其他设计方法，基于被控对象模型设计控制器。
使用时域和频域中的超调、上升时间、相位裕度、增益裕度及其他性能和稳定性特性，以交互方式分析控制系统性能。
自动调节 PID、增益调度和任意 SISO 和 MIMO 控制系统。
设计和实现稳健的模型预测控制器或使用无模型控制方法，如模型引用自适应控制、极值搜索控制、强化学习和模糊逻辑。
将控制算法部署到嵌入式系统，用于实时控制、调节或参数估计。
设计和测试状态监控与预测性维护算法。

适用产品: 控制系统

Control System Toolbox

设计和分析控制系统

System Identification Toolbox

Create linear and nonlinear dynamic system models from input-output data

Predictive Maintenance Toolbox

Design and test condition monitoring and predictive maintenance algorithms

Robust Control Toolbox

Design robust controllers for uncertain plants

Model Predictive Control Toolbox

Design and simulate model predictive controllers

Fuzzy Logic Toolbox

Design and simulate fuzzy logic systems

Simulink Control Design

线性化模型和设计控制系统

Simulink Design Optimization

Analyze model sensitivity and tune model parameters

Reinforcement Learning Toolbox

Design and train policies using reinforcement learning

Motor Control Blockset

设计和实现电机控制算法

C2000 Microcontroller Blockset

Design, simulate, and implement applications for Texas Instruments C2000 microcontrollers

主题

被控对象建模、系统辨识和参数估计

使用模型对象进行控制系统建模 (Control System Toolbox)
使用模型对象构建表示您的控制系统的模型。
Analyze Data in Multivariable Systems and Identify Models (System Identification Toolbox)
Collect MIMO data, estimate and compare models, and view corresponding model responses.
Online ARX Parameter Estimation for Tracking Time-Varying System Dynamics (System Identification Toolbox)
Perform online parameter estimation for a time-varying ARX model at the MATLAB command line.
Inverted Pendulum Parameter Estimation (Simulink Design Optimization)
Estimate multiple parameters of a model by iterated estimations.

配平、线性化和频率响应估计

Compute Operating Points from Specifications Using Steady State Manager (Simulink Control Design)
Find steady-state operating points that meet specifications by trimming your Simulink model using the Steady State Manager app.
在模型工作点处线性化 Simulink 模型 (Simulink Control Design)
在由初始状态值和输入信号组成的工作点处线性化模型。
Frequency Response Estimation in Model Linearizer Using Pseudorandom Binary Sequence (Simulink Control Design)
Identify a frequency-domain model for a high-frequency power electronics system using a PRBS input signal in Model Linearizer.

控制设计和调节

Root Locus Design (Control System Toolbox)
Design a compensator for an electrohydraulic servomechanism using root locus graphical tuning techniques.
Design Compensator Using Automated Tuning Methods (Control System Toolbox)
Tune a compensator using automated tuning methods in Control System Designer.
Tune Control Systems Using systune (Control System Toolbox)
Use systune to tune structured controllers for a simple application.
Design Controller for Power Electronics Model Using Simulated I/O Data (Simulink Control Design)
Use PID Tuner to identify a plant model and design a PID controller for a power electronics model that cannot be linearized.
Tune Gain-Scheduled Controller Using Closed-Loop PID Autotuner Block (Simulink Control Design)
Use Closed-Loop PID Autotuner block to tune gain-scheduled PID controller for a water-tank model in one simulation.

预测与稳健控制

Design MPC Controller in Simulink (Model Predictive Control Toolbox)
Design and simulate a model predictive controller for a Simulink model using MPC Designer.
Robust Control of Active Suspension (Robust Control Toolbox)
In this example, use H_∞ synthesis to design a controller for a nominal plant model. Then, use μ synthesis to design a robust controller that accounts for uncertainty in the model.

自适应与智能控制

Model Reference Adaptive Control of Aircraft Undergoing Wing Rock (Simulink Control Design)
Design an MRAC controller that adapts disturbance model parameters to achieve performance matching an ideal reference model.
Design and Train Agent Using Reinforcement Learning Designer (Reinforcement Learning Toolbox)
Design and train a DQN agent for a cart-pole system using the Reinforcement Learning Designer app.
Design Controller for Artificial Pancreas Using Fuzzy Logic (Fuzzy Logic Toolbox)
Design and tune a FIS tree to control insulin infusion for type-1 diabetes.

可部署算法

Tune PI Controllers Using Field Oriented Control Autotuner Block on Real-Time Systems (Motor Control Blockset)
Compute the gain values of PI controllers within the speed and current controllers by using the Field Oriented Control Autotuner block.
Simulation and Code Generation Using Simulink Coder (Model Predictive Control Toolbox)
Simulate your MPC controller in Simulink and generate real-time code that uses either double-precision or single-precision signals.
Parameter Tuning for Digital Twins (Simulink Design Optimization)
Monitor the condition of an electric vehicle battery in the field with a deployed version of parameter estimation using Simulink Compiler™.

精选示例

Multiloop Control of a Helicopter

Use slTuner and systune to tune a multi-loop controller for a rotorcraft.

(Control System Toolbox)

Design PID Controllers for Three-Phase Rectifier Using Closed-Loop PID Autotuner Block

Tune controllers for a Vienna-rectifier-based power factor corrector using the Closed-Loop PID Autotuner block.

(Simulink Control Design)

Adaptive Cruise Control Using Extremum Seeking Control

Design an extremum seeking controller to adjust controller gains for an adaptive cruise control system.

(Simulink Control Design)

Control PMSM Loaded with Dual Motor (Dyno) Using C2000 Processors

Uses field-oriented control (FOC) to control two three-phase permanent magnet synchronous motors (PMSM) coupled in a dyno setup. Motor 1 runs in the closed-loop speed control mode. Motor 2 runs in the torque control mode and loads Motor 1 because they are mechanically coupled. You can use this example to test a motor in different load conditions.

(C2000 Microcontroller Blockset)